Abstract: Speech recognition is applied in many systems. In an environment without occurrence of noise, high recognition accuracy is achieved. However in noisy environments, it commonly shows a poor performance. To improve the performance of recognition system in noisy environments, we need a noise-robust speech representation. From this point of view, many methods have been proposed up to now. However, unfortunately, we are still struggling to find the robust speech representation form. Recently, Shannon and Paliwal proposed Autocorrelation Mel-frequency Cepstral Coefficients (AMFCC) method that uses higher-lag autocorrelation sequence as the input of Mel-frequency filter bank analysis to find Mel-frequency Cepstral Coefficients (MFCC) spectral representation. The recognizers that use this kind of spectral representations showed a better performance rather than the typical MFCC analysis directly on the speech signal. In this plenary speech, several robust speech representations are discussed, which include the MFCC and AMFCC spectral representations. And it is presented that robust features of speech are correlation functions and their modifications. Also, for the purpose of improving the performance of speech recognition in noisy environments, two methods using Autocorrelation and Double Autocorrelation sequences as the input of a Mel-frequency filter bank analysis to find MFCC spectral feature are derived. A word recognition experiment validates that both of the proposed methods achieve better results than the conventional MFCC spectral analysis on the input speech signal.

Brief Biography of the Speaker:
Tetsuya Shimamura received the B.E., M.E., and Ph. D. degrees in electrical engineering from Keio University, Yokohama, Japan, in 1986, 1988, and 1991, respectively. In 1991, he joined Saitama University, Saitama City, Japan, where he is currently a Professor. During this, he joined Loughborough University, UK, and The Queen’s University of Belfast, UK, in 1995 and 1996, respectively, as a visiting Professor. He is an author or co-author of 6 books, and member of the organizing committee of several international conferences. His interests are in digital signal processing and its applications to speech, image and communication systems.